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Gallium nitride (GaN) is a compound semiconductor that has tremendous potential to facilitate economic growth in a semiconductor industry that is silicon-based and currently faced with diminishing returns of performance versus cost of investment. At a material level, its high electric field strength and electron mobility have already shown tremendous potential for high frequency communications and photonic applications. Advances in growth on commercially viable large area substrates are now at the point where power conversion applications of GaN are at the cusp of commercialisation. The future for building on the work described here in ways driven by specific challenges emerging from entirely new markets and applications is very exciting. This collection of GaN technology developments is therefore not itself a road map but a valuable collection of global state-of-the-art GaN research that will inform the next phase of the technology as market driven requirements evolve. First generation production devices are igniting large new markets and applications that can only be achieved using the advantages of higher speed, low specific resistivity and low saturation switching transistors. Major investments are being made by industrial companies in a wide variety of markets exploring the use of the technology in new circuit topologies, packaging solutions and system architectures that are required to achieve and optimise the system advantages offered by GaN transistors. It is this momentum that will drive priorities for the next stages of device research gathered here.

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Integrating a battery energy storage system (BESS) with a large wind farm can smooth out the intermittent power from the wind farm. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers a conventional feedback-based control scheme with revisions to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge rate, and lifetime. The goal of the control is to have the BESS provide as much smoothing as possible so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Finally, it is shown that the control strategy is very important in determining the proper BESS size needed for this application.

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Integrating a battery energy storage system (BESS) with a large wind farm can make a wind farm more dispatchable. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers an open-loop optimal control scheme to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge current limits, and lifetime. The goal of the control is to have the BESS to provide as much smoothing as possible, so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Furthermore, a real-time implementation strategy using model predictive control is also proposed. Finally, it is shown that the control strategy is very important in improving the BESS performance for this application.Index Terms-Battery energy storage system (BESS), dispatchability, model predictive control (MPC), optimal control, wind energy.

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